'''Question-1'''
import seaborn as sns
titanic = sns.load_dataset('titanic')
titanic.head()
| survived | pclass | sex | age | sibsp | parch | fare | embarked | class | who | adult_male | deck | embark_town | alive | alone | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0 | 3 | male | 22.0 | 1 | 0 | 7.2500 | S | Third | man | True | NaN | Southampton | no | False |
| 1 | 1 | 1 | female | 38.0 | 1 | 0 | 71.2833 | C | First | woman | False | C | Cherbourg | yes | False |
| 2 | 1 | 3 | female | 26.0 | 0 | 0 | 7.9250 | S | Third | woman | False | NaN | Southampton | yes | True |
| 3 | 1 | 1 | female | 35.0 | 1 | 0 | 53.1000 | S | First | woman | False | C | Southampton | yes | False |
| 4 | 0 | 3 | male | 35.0 | 0 | 0 | 8.0500 | S | Third | man | True | NaN | Southampton | no | True |
import plotly.express as px
# Plot a scatter plot for "age" and "fare" columns using Plotly express
fig = px.scatter(titanic,
x="age",
y="fare",
title="Titanic Dataset: Age vs. Fare")
# Update the layout to center the title above the plot
fig.update_layout(
title={
'text': "Titanic Dataset: Age vs. Fare",
'y':0.95,
'x':0.5,
'xanchor': 'center',
'yanchor': 'top'})
fig.show()
'''Question-2'''
'Question-2'
import plotly.express as px
tips = px.data.tips()
tips.head()
| total_bill | tip | sex | smoker | day | time | size | |
|---|---|---|---|---|---|---|---|
| 0 | 16.99 | 1.01 | Female | No | Sun | Dinner | 2 |
| 1 | 10.34 | 1.66 | Male | No | Sun | Dinner | 3 |
| 2 | 21.01 | 3.50 | Male | No | Sun | Dinner | 3 |
| 3 | 23.68 | 3.31 | Male | No | Sun | Dinner | 2 |
| 4 | 24.59 | 3.61 | Female | No | Sun | Dinner | 4 |
# Plot a box plot for the "total_bill" column using Plotly express
fig = px.box(tips,x='day',y="total_bill", title="Tips Dataset: Total Bill Box Plot")
fig.show()
'''Question-3'''
'Question-3'
# Plot a histogram for "sex" and "total_bill" columns using Plotly express
fig = px.histogram(tips, x="sex", y="total_bill",
color="day", pattern_shape="smoker",
title="Tips Dataset: Total Bill by Gender and Smoking Status")
fig.show()
'''Quetion-4'''
'Quetion-4'
pip install plotly --upgrade
Requirement already satisfied: plotly in /opt/homebrew/anaconda3/lib/python3.11/site-packages (5.9.0) Collecting plotly Obtaining dependency information for plotly from https://files.pythonhosted.org/packages/a8/07/72953cf70e3bd3a24cbc3e743e6f8539abe6e3e6d83c3c0c83426eaffd39/plotly-5.18.0-py3-none-any.whl.metadata Downloading plotly-5.18.0-py3-none-any.whl.metadata (7.0 kB) Requirement already satisfied: tenacity>=6.2.0 in /opt/homebrew/anaconda3/lib/python3.11/site-packages (from plotly) (8.2.2) Requirement already satisfied: packaging in /opt/homebrew/anaconda3/lib/python3.11/site-packages (from plotly) (23.1) Downloading plotly-5.18.0-py3-none-any.whl (15.6 MB) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 15.6/15.6 MB 7.8 MB/s eta 0:00:0000:0100:01 Installing collected packages: plotly Attempting uninstall: plotly Found existing installation: plotly 5.9.0 Uninstalling plotly-5.9.0: Successfully uninstalled plotly-5.9.0 Successfully installed plotly-5.18.0 Note: you may need to restart the kernel to use updated packages.
import plotly.express as px
# Load the "iris" dataset from Plotly
iris = px.data.iris()
# Plot a scatter matrix plot using Plotly express
fig = px.scatter_matrix(
iris,
dimensions=["sepal_length", "sepal_width", "petal_length", "petal_width"],
color="species",
title="Iris Dataset: Scatter Matrix Plot"
)
# Show the plot
fig.show()
'''Question-5'''
'''
In Plotly Express, the distplot function is used to create a distribution plot (histogram) for univariate data.
It provides a visual representation of the distribution of a single continuous variable.
The distplot combines a histogram with a kernel density estimate (KDE) to give a smooth representation of the underlying distribution.'''
import plotly.express as px
tips = px.data.tips()
fig = px.histogram(tips, x="total_bill", y="tip", color="sex",
marginal="box", # or violin, rug
hover_data=tips.columns)
fig.show()